On one hand, for DS engines, each result will map
one-to-one with existing technologies in the repository via its
name and repository_url. On the other hand, for GP engines, the search results are Web documents,
which might refer to zero, one or many technologies. For this reason,
those names of the technologies should be recovered. This information extraction task can be seen as a Named Entity Recognition (NER) problem. NER [1]} aims at classifying entities found in a given text into predefined categories (e.g., people, organizations, places, time expressions, among others). In our work, the named entity category is "software
technology", and we employ a rule-based strategy for string-matching
[2]}. By means of these rules, all the
technologies whose name or address (home_url, repository_url)
match the category are extracted.
